Title :
A Genetic Algorithm For Minimizing The Weighted Number Of Tardy Jobs
Author :
Desprez, Caroline ; Chu, Chengbin ; Chu, Feng
Author_Institution :
Inst. Charles Delaunay, Univ. de technologie de Troyes
Abstract :
This paper deals with a flow shop in which each operation needs several resources, some of these resources being polyvalent. The objective is to minimize the weighted number of tardy jobs. This problem represents a real industrial issue. The production system studied can be found in many companies. Currently, the firm that set the problem is using an industrial software. Our aim is to find a quick method to obtain better results than with this software. Because of the problem size and complexity, we decided to use a genetic algorithm to solve it. In this paper, we present this algorithm and we give some results obtained with it. Then we compare these results with those obtained with the software. These results show a clear improvement of the solution quality with the genetic algorithm
Keywords :
computational complexity; flow shop scheduling; genetic algorithms; manufacturing systems; minimisation; flow shop scheduling; genetic algorithm; industrial software; production system; tardy job minimization; Aggregates; Computer industry; Genetic algorithms; Job shop scheduling; Manufacturing industries; Painting; Production systems; Resource management; Testing; Welding; Genetic Algorithm; multi-resource; re-entrant resources; weighted number of tardy jobs;
Conference_Titel :
Service Systems and Service Management, 2006 International Conference on
Conference_Location :
Troyes
Print_ISBN :
1-4244-0450-9
Electronic_ISBN :
1-4244-0451-7
DOI :
10.1109/ICSSSM.2006.320691
